Fibre-based fluorescence-lifetime imaging microscopy - a real-time biopsy guidance tool for suspected lung cancer

Q: Why is early detection important in suspected lung cancer?

Early detection improves clinical outcomes by enabling timely diagnosis and treatment. Low-dose computed tomography screening reduces lung cancer mortality through early detection and subsequent management.

Q: What technique does the study evaluate for biopsy guidance?

The study evaluates fibre-based fluorescence-lifetime imaging microscopy (FLIM), which measures fluorescence lifetime from endogenous autofluorescence to support distinguishing cancerous tissue from adjacent healthy tissue.

Q: How does the fibre-based system aim to improve biopsy sampling?

By providing real-time visualisation and quantitative lifetime analysis, the system supports identifying optimal biopsy sites and distinguishing ex vivo lung cancer from non-cancerous lung tissue to enhance diagnostic accuracy.

Sep 21, 2026

Uploaded by Lucas Martin

Lung cancer causes the greatest number of cancer-related deaths worldwide, and early detection improves outcomes. Existing sampling methods can yield suboptimal diagnostic results and may lead to procedure-related complications. Autofluorescence-based fluorescence-lifetime imaging microscopy (FLIM) measures endogenous fluorophore decay rates and may help identify optimal biopsy sites in suspected lung cancer.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages7

Reading Time18 min

AccessFree to download

Introduction

Background on lung cancer screening and diagnosis

Advances in bronchoscopy and imaging guidance

Fibre-based optical techniques and FLIM

Fibre-based fluorescence-lifetime imaging microscopy: areal-time biopsy guidance tool for suspected lung cancer Susan Fernandes 1,2 ^, Elvira Williams 1 , Neil Finlayson 1,3 ^, Hazel Stewart 1 ^, Catharine Dhaliwal4 , David A. Dorward 1,5, William A. Wallace5, Ahsan R. Akram 1,2^, James Stone 1,6^, Kevin Dhaliwal 1,2^, Gareth O. S. Williams1^ 1Translational Healthcare Technologies Group, Centre for Inflammation Research, Institute for Regeneration and Repair, The University of Edinburgh, Edinburgh, UK; 2Department of Respiratory Medicine, NHS Lothian, Royal Infirmary of Edinburgh, Edinburgh, UK; 3Institute for Integrated Micro and Nano Systems, School of Engineering, The University of Edinburgh, Edinburgh, UK; 4Department of Pathology, NHS Lothian, Western General Hospital, Edinburgh, UK; 5Department of Pathology, NHS Lothian, Royal Infirmary of Edinburgh, Edinburgh, UK; 6Centre for Photonics and Photonic Materials, Department of Physics, The University of Bath, Bath, UK Correspondence to: Gareth O. S. Williams, PhD. Translational Healthcare Technologies Group, Centre for Inflammation Research, Institute for Regeneration and Repair, The University of Edinburgh, 4-5 Little France Drive, Edinburgh, EH16 4UU, [UK. Email: G.O.S.Williams@ed.ac.uk](UK. Email: G.O.S.Williams@ed.ac.uk); Kevin Dhaliwal, MD, PhD. Translational Healthcare Technologies Group, Centre for Inflammation Research, Institute for Regeneration and Repair, The University of Edinburgh, 4-5 Little France Drive, Edinburgh, EH16 4UU, UK; Department of Respiratory Medicine, NHS Lothian, Royal Infirmary of Edinburgh, 51 Little France Crescent, Edinburgh, EH16 4SA, UK. Email: kev.[dhaliwal@ed.ac.uk](dhaliwal@ed.ac.uk). Abstract: Lung cancer is the most common cause of cancer-related deaths worldwide. Early detection improves outcomes, however, existing sampling techniques are associated with suboptimal diagnostic yield and procedure-related complications. Autofluorescence-based fluorescence-lifetime imaging microscopy (FLIM), a technique which measures endogenous fluorophore decay rates, may aid identification of optimal biopsy sites in suspected lung cancer. Our fibre-based fluorescence-lifetime imaging system, utilising 488 nm excitation, which is deliverable via existing diagnostic platforms, enables real-time visualisation and lifetime analysis of distal alveolar lung structure. We evaluated the diagnostic accuracy of the fibre-based fluorescence-lifetime imaging system to detect changes in fluorescence lifetime in freshly resected ex vivo lung cancer and adjacent healthy tissue as a first step towards future translation. The study compares paired non-small cell lung cancer (NSCLC) and non-cancerous tissues with gold standard diagnostic pathology to assess the performance of the technique. Paired NSCLC and non-cancerous lung tissues were obtained from thoracic resection patients (N=21) . A clinically compatible 488 nm fluorescence-lifetime endomicroscopy platform was used to acquire simultaneous fluorescence intensity and lifetime images. Fluorescence lifetimes were calculated using a computationally-lightweight, rapid lifetime determination method. Fluorescence lifetime was significantly reduced in ex vivo lung cancer, compared with non-cancerous lung tissue [mean ± standard deviation (SD), 1.79±0.40 vs. 2.15±0.26 ns, P<0.0001], and fluorescence intensity images demonstrated distortion of alveolar elastin autofluorescence structure. Fibre-based fluorescence-lifetime imaging demonstrated good performance characteristics for distinguishing lung cancer, from adjacent noncancerous tissue, with 81.0% sensitivity and 71.4% specificity. Our novel fibre-based fluorescence-lifetime imaging system, which enables label-free imaging and quantitative lifetime analysis, discriminates ex vivo lung cancer from adjacent healthy tissue. This minimally invasive technique has potential to be translated as a real-time biopsy guidance tool, capable of optimising diagnostic accu

FAQs

Why is early detection important in suspected lung cancer?

Early detection improves clinical outcomes by enabling timely diagnosis and treatment. Low-dose computed tomography screening reduces lung cancer mortality through early detection and subsequent management.

What technique does the study evaluate for biopsy guidance?

The study evaluates fibre-based fluorescence-lifetime imaging microscopy (FLIM), which measures fluorescence lifetime from endogenous autofluorescence to support distinguishing cancerous tissue from adjacent healthy tissue.

How does the fibre-based system aim to improve biopsy sampling?

By providing real-time visualisation and quantitative lifetime analysis, the system supports identifying optimal biopsy sites and distinguishing ex vivo lung cancer from non-cancerous lung tissue to enhance diagnostic accuracy.

Sep 21, 2026

Uploaded by Lucas Martin